---
title: "Write a clear and informative project title here"
subtitle: "MATH 3570 Intro to Data Science Spring 2026"
author: "Your Team Name"
date: today
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    fontsize: 11pt
    linestretch: 1.15
execute:
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---

Replace all bracketed text with your own writing. Delete any instructional notes that are not part of your final report.

# Introduction

\[In 1 to 3 paragraphs, introduce the topic, explain why it matters, and state the main goal of the project.\]

## Research Question

\[State your one main question clearly. Keep the project focused.\]

# Data Description

## Data Source

\[Explain where the data came from. Include the source name, website, organization, or publication if applicable.\]

## Observational Units

\[Explain what one row of the data represents. For example, one person, one house, one song, one county, and so on.\]

## Key Variables

\[Briefly describe the most important variables used in your project. You do not need to list every variable in the full dataset, only the variables that matter for your analysis.\]

## Data Limitations or Quality Concerns

\[Briefly discuss any important issues in the dataset, such as missing values, measurement problems, unclear definitions, limited scope, or possible bias.\]

# Data Preparation

\[Explain how you prepared the data for analysis. Write this as a clear narrative, not only as code.\]

Possible items to describe if relevant:

-   handling missing values
-   filtering observations
-   recoding variables
-   reshaping data
-   joining datasets
-   creating new variables

## Summary of Data Preparation

\[Write 1 short paragraph summarizing the most important preparation steps and why they were necessary.\]

# Exploratory Analysis

\[Use this section to help the reader understand the data before you apply a method. Each figure or table should have a clear purpose and should be discussed in words.\]

## Summary Table

\[Insert at least 1 summary table here. Introduce it in words and explain what the reader should notice.\]

## Figure 1

\[Insert Figure 1 here. Then explain what the figure shows and why it matters for your project question.\]

## Figure 2

\[Insert Figure 2 here. Then explain what the figure shows and why it matters for your project question.\]

## Figure 3

\[Insert Figure 3 here. Then explain what the figure shows and why it matters for your project question.\]

\[Add more figures if they are useful, but do not include plots only to fill space.\]

# Method

\[Explain the method or methods you used. Use clear language. The goal is to show that you understand what the method does and why it is appropriate for your question.\]

## Chosen Method

\[Name the method here, such as multiple linear regression, logistic regression, decision tree, k-nearest neighbors, principal component analysis, or k-means clustering.\]

## Why This Method Was Used

\[Explain why this method fits your project question and your data.\]

## Important Details

\[Briefly explain any key choices you made, such as predictor variables, training and testing split, tuning choices, selected number of clusters, or principal components interpreted.\]

# Results

\[Present the main findings from your method. Focus on the results that help answer your question.\]

## Main Findings

\[Explain the most important results in plain language.\]

## Interpretation

\[Interpret the results carefully in context. Avoid overstating what the analysis shows. Be especially careful about prediction versus explanation and association versus causation.\]

# Limitations

\[Discuss important limitations of the data, method, and conclusions. This section should be honest and thoughtful.\]

Possible ideas to discuss if relevant:

-   missing information
-   possible bias
-   model assumptions
-   measurement error
-   limited generalizability
-   small sample size
-   uncertainty in the conclusions

# Conclusion

\[Write a short conclusion that answers the main project question as clearly as possible. Summarize the most important takeaway in plain language.\]

# References

\[List any sources you used, such as the dataset source, articles, documentation, or other references.\]

# Appendix A. AI Use Statement

Our team used the following AI tool or tools: \[name of tool or tools\].

AI was used for the following tasks:

-   \[example: brainstorming possible project questions\]
-   \[example: helping explain code errors\]
-   \[example: improving wording or editing sentences\]
-   \[example: suggesting visualization ideas\]

To check and revise the AI output, our team:

-   \[example: verified results using our own code and analysis\]
-   \[example: corrected inaccurate or vague explanations\]
-   \[example: rewrote parts of the text in our own words\]
-   \[example: compared suggestions against course materials and dataset documentation\]

Final responsibility for the accuracy and clarity of the report remained with our team.

# Appendix B. Team Contribution Statement

Use the format below and revise it to match your project honestly.

-   **Team Member 1 Name:** \[main contributions\]
-   **Team Member 2 Name:** \[main contributions\]
-   **Team Member 3 Name:** \[main contributions\]

\[Add 1 to 2 sentences describing how your team divided the work, communicated, and reviewed the final report together. If contributions were not fully equal, state that professionally and honestly.\]